Literature DB >> 17105983

Age-related lobular involution and risk of breast cancer.

Tia R Milanese1, Lynn C Hartmann, Thomas A Sellers, Marlene H Frost, Robert A Vierkant, Shaun D Maloney, V Shane Pankratz, Amy C Degnim, Celine M Vachon, Carol A Reynolds, Romayne A Thompson, L Joseph Melton, Ellen L Goode, Daniel W Visscher.   

Abstract

BACKGROUND: As women age, the lobules in their breasts undergo involution or regression. We investigated whether lobular involution in women with benign breast disease was associated with subsequent breast cancer risk.
METHODS: We examined biopsy specimens of 8736 women in the Mayo Benign Breast Disease Cohort from whom biopsy samples were taken between January 1, 1967, and December 31, 1991. Median follow-up for breast cancer outcomes was 17 years. We classified lobular involution in the background breast tissue as none (0% involuted lobules), partial (1%-74%), or complete (> or = 75%). Subsequent breast cancer events and data on other risk factors were obtained from medical records and follow-up questionnaires. To estimate relative risks (RRs), standardized incidence ratios were calculated by use of incidence rates from the Iowa Surveillance, Epidemiology, and End Results (SEER) Registry. All statistical tests were two-sided.
RESULTS: Distribution of extent of involution was none among 1627 (18.6%) women, partial among 5197 (59.5%), and complete among 1912 (21.9%). Increased involution was positively associated with increased age and inversely associated with parity (both P<.001). The relative risk for the entire cohort of 8736 women, compared with the Iowa SEER population, was 1.40 (95% CI = 1.30 to 1.51). Risk of breast cancer was associated with the extent of involution (for no involution, RR [i.e., observed versus expected] = 1.88, 95% confidence interval [CI] = 1.59 to 2.21; for partial involution, RR = 1.47, 95% CI = 1.33 to 1.61; and for complete involution, RR = 0.91, 95% CI = 0.75 to 1.10; test for heterogeneity P<.001). Lobular involution modified risk in all subsets (e.g., among women with atypia, for no involution, RR = 7.79, 95% CI = 3.56 to 14.81; for partial involution, RR = 4.06, 95% CI = 3.03 to 5.33; and for complete involution, RR = 1.49, 95% CI = 0.41 to 3.82; P = .003).
CONCLUSIONS: In this large cohort of women with benign breast disease, lobular involution was associated with reduced risk of breast cancer. Aberrant involution may be a biologically important phenomenon in breast cancer biology.

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Year:  2006        PMID: 17105983     DOI: 10.1093/jnci/djj439

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  138 in total

1.  Lobular involution, mammographic density, and breast cancer risk: visualizing the future?

Authors:  Gretchen L Gierach; Louise A Brinton; Mark E Sherman
Journal:  J Natl Cancer Inst       Date:  2010-10-29       Impact factor: 13.506

Review 2.  Breast tissue composition and susceptibility to breast cancer.

Authors:  Norman F Boyd; Lisa J Martin; Michael Bronskill; Martin J Yaffe; Neb Duric; Salomon Minkin
Journal:  J Natl Cancer Inst       Date:  2010-07-08       Impact factor: 13.506

3.  Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use.

Authors:  Karla Kerlikowske; Andrea J Cook; Diana S M Buist; Steve R Cummings; Celine Vachon; Pamela Vacek; Diana L Miglioretti
Journal:  J Clin Oncol       Date:  2010-07-19       Impact factor: 44.544

4.  Quantitative Analysis of TDLUs using Adaptive Morphological Shape Techniques.

Authors:  Adrian Rosebrock; Jesus J Caban; Jonine Figueroa; Gretchen Gierach; Laura Linville; Stephen Hewitt; Mark Sherman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-29

5.  ERβ expression and breast cancer risk prediction for women with atypias.

Authors:  Tina J Hieken; Jodi M Carter; John R Hawse; Tanya L Hoskin; Melanie Bois; Marlene Frost; Lynn C Hartmann; Derek C Radisky; Daniel W Visscher; Amy C Degnim
Journal:  Cancer Prev Res (Phila)       Date:  2015-08-14

6.  Lobule type and subsequent breast cancer risk: results from the Nurses' Health Studies.

Authors:  Heather J Baer; Laura C Collins; James L Connolly; Graham A Colditz; Stuart J Schnitt; Rulla M Tamimi
Journal:  Cancer       Date:  2009-04-01       Impact factor: 6.860

7.  Ki67: a time-varying biomarker of risk of breast cancer in atypical hyperplasia.

Authors:  Marta Santisteban; Carol Reynolds; Emily G Barr Fritcher; Marlene H Frost; Robert A Vierkant; Stephanie S Anderson; Amy C Degnim; Daniel W Visscher; V Shane Pankratz; Lynn C Hartmann
Journal:  Breast Cancer Res Treat       Date:  2009-09-23       Impact factor: 4.872

8.  Relationship between clinical and pathologic features of ductal carcinoma in situ and patient age: an analysis of 657 patients.

Authors:  Laura C Collins; Ninah Achacoso; Larissa Nekhlyudov; Suzanne W Fletcher; Reina Haque; Charles P Quesenberry; Balaram Puligandla; Najeeb S Alshak; Lynn C Goldstein; Allen M Gown; Stuart J Schnitt; Laurel A Habel
Journal:  Am J Surg Pathol       Date:  2009-12       Impact factor: 6.394

9.  Assessment of the accuracy of the Gail model in women with atypical hyperplasia.

Authors:  V Shane Pankratz; Lynn C Hartmann; Amy C Degnim; Robert A Vierkant; Karthik Ghosh; Celine M Vachon; Marlene H Frost; Shaun D Maloney; Carol Reynolds; Judy C Boughey
Journal:  J Clin Oncol       Date:  2008-10-14       Impact factor: 44.544

Review 10.  Mammary gland development.

Authors:  Hector Macias; Lindsay Hinck
Journal:  Wiley Interdiscip Rev Dev Biol       Date:  2012 Jul-Aug       Impact factor: 5.814

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